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ML Annotation QA Engineer

Gather AI
Location
Open to Remote (India)
Posted
16 days ago
Department
Quality Assurance
What they actually want (must-haves)
  • BS in Computer Science/Engineering, Electrical Engineering, or equivalent experience
  • 2–5 years of experience in ML QA, annotation quality, data quality, or analytics at an AI/ML company
  • Hands-on experience with annotated ML datasets, including assessing label quality
  • Demonstrated experience finding, diagnosing, and reporting data anomalies to a technical audience
  • Strong understanding of statistics, and able to work with data
  • Root cause analysis — generating competing hypotheses and naming the evidence that separates them
Nice to have
  • 2+ years in quality assurance, data quality, or product support
  • 1+ years experience with enterprise-grade ticketing systems (e.g. Jira)
  • Computer vision annotation experience as a reviewer or auditor — video event labeling, bounding boxes, polygon segmentation, counting, or classification
  • Annotation quality methodology — gold-set validation, inter-annotator agreement, sampling design
  • Strong spatial and geometric reasoning — relevant wherever labels describe position in physical space
What the job really is

As an ML Annotation QA Engineer at Gather AI, you will be responsible for ensuring the quality of annotated data used in computer vision and machine learning programs. Your day-to-day tasks will include analyzing annotated data, conducting root cause analysis, and developing performance trackers to monitor data quality. You will collaborate closely with Machine Learning Engineers and other teams to identify and address anomalies in the data, refine decision rules, and improve annotation processes.

Things to weigh
  • Role involves significant judgment and analysis that cannot be outsourced, indicating a high level of responsibility.
  • The position requires a strong analytical mindset and the ability to work under ambiguity, which may not suit all candidates.
  • No salary or benefits information provided in the posting.
Job score2.8/5
Benefits1/5
Freshness4/5
Career value4/5
Role clarity5/5
Pay transparency0/5

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